Pairwise Check Decoding for LDPC Coded Two-Way Relay Block Fading Channels

Partial decoding has the potential to achieve a larger capacity region than full decoding in two-way relay (TWR) channels. Existing partial decoding realizations are however designed for Gaussian channels and with a static physical layer network coding (PLNC). In this paper, we propose a new solution for joint network coding and channel decoding at the relay, called pairwise check decoding (PCD), for low-density parity-check (LDPC) coded TWR system over block fading channels. The main idea is to form a check relationship table (check-relation-tab) for the superimposed LDPC coded packet pair in the multiple access (MA) phase in conjunction with an adaptive PLNC mapping in the broadcast (BC) phase. Using PCD, we then present a partial decoding method, two-stage closest-neighbor clustering with PCD (TS-CNC-PCD), with the aim of minimizing the worst pairwise error probability. Moreover, we propose the minimum correlation optimization (MCO) for selecting the better check-relation-tabs. Simulation results confirm that the proposed TS-CNC-PCD offers a sizable gain over the conventional XOR with belief propagation (BP) in fading channels.Comment: to appear in IEEE Trans. on Communications, 201

Transmission of Analog Information Over the Multiple Access Relay Channel Using Zero-Delay Non-Linear Mappings

[Abstract]: We consider the zero-delay encoding of discrete-time analog information over the Multiple Access Relay Channel (MARC) using non-linear mapping functions. On the one hand, zero-delay non-linear mappings are capable to deal with the multiple access interference (MAI) caused by the simultaneous transmission of the information. On the other, the relaying operation is a Decode-and-Forward (DF) strategy where the decoded messages are merged into a single message using a specific continuous mapping depending on the correlation level of the source information. At the receiver, an approximated Minimum Mean Squared Error (MMSE) decoder is developed to obtain an estimate of the transmitted source symbols which exploits the information received from the relay node in combination with the messages received from the transmitters through the direct links. The resulting system provides better performance than the other alternative encoding strategies for the MARC with similar complexity and delay and also approaches the performance of theoretical strategies which require a significantly higher delay and computational cost.This work was supported in part by the Office of the Naval Research Global of United States under Grant N62909-15-1-2014, in part by the Xunta de Galicia under Grant ED431C 2016-045, Grant ED341D R2016/012, and Grant ED431G/01, in part by the Agencia Estatal de Investigación of Spain under Grant TEC2015-69648-REDC and Grant TEC2016-75067-C4-1-R, and in part by the ERDF funds of the EU (AEI/FEDER, UE).Xunta de Galicia; ED431C 2016-045Xunta de Galicia; ED341D R2016/012Xunta de Galicia; ED431G/0

Relay selection for multiple access relay channel with decode-forward and analog network coding

This paper presents a relay selection for decode-and-forward based on network coding (DF-NC) and analog-NC protocols in general scheme of cellular network system. In the propose scheme the two source node simultaneously transmit their own information to all the relays as well as the destination node, and then, a single relay i.e. best with a minimum symbol error rate (SER) will be selected to forward the new version of the received signal. Simulation results show that, the DF-NC scheme with considerable performance has exactness over analog-NC scheme. To improve the system performance, optimal power allocation between the two sources and the best relay is determined based on the asymptotic SER. By increasing the number of relays node, the optimum power allocation achieve better performance than asymptotic SER.Comment: 11 pages, 5 figures; International Journal of Distributed and Parallel Systems (IJDPS) Vol.3, No.2, March 201

Reduced-Dimension Linear Transform Coding of Correlated Signals in Networks

A model, called the linear transform network (LTN), is proposed to analyze the compression and estimation of correlated signals transmitted over directed acyclic graphs (DAGs). An LTN is a DAG network with multiple source and receiver nodes. Source nodes transmit subspace projections of random correlated signals by applying reduced-dimension linear transforms. The subspace projections are linearly processed by multiple relays and routed to intended receivers. Each receiver applies a linear estimator to approximate a subset of the sources with minimum mean squared error (MSE) distortion. The model is extended to include noisy networks with power constraints on transmitters. A key task is to compute all local compression matrices and linear estimators in the network to minimize end-to-end distortion. The non-convex problem is solved iteratively within an optimization framework using constrained quadratic programs (QPs). The proposed algorithm recovers as special cases the regular and distributed Karhunen-Loeve transforms (KLTs). Cut-set lower bounds on the distortion region of multi-source, multi-receiver networks are given for linear coding based on convex relaxations. Cut-set lower bounds are also given for any coding strategy based on information theory. The distortion region and compression-estimation tradeoffs are illustrated for different communication demands (e.g. multiple unicast), and graph structures.Comment: 33 pages, 7 figures, To appear in IEEE Transactions on Signal Processin